Model-Driven Quality Analysis of Cyber-Physical Systems: State of the Art and Perspectives

Analyzing quality attributes in Cyber-Physical Systems (CPS) is essential for ensuring their efficiency, and resilience. This paper presents an exploratory study of the current state of the art in CPS quality analysis, with a particular emphasis on the use of annotated models and the role of Digital Twins (DTs). Through a rigorous selection and filtering process, 11 key publications from the past six years were identified as foundational contributions to the field. These studies offer valuable insights into prevailing methodologies, recurring challenges, and emerging trends, illustrating how annotated models and DTs can enhance the assessment and management of CPS quality attributes. This work lays the groundwork for future research into more effective model-driven approaches and techniques for evaluating and improving CPS quality, potentially leveraging the capabilities of DTs.